Genes, enzymes and chemicals of terpenoid diversity in the constitutive and induced defence of conifers against insects and pathogens*
Bibliographic record
Abstract
Insects select their hosts, but trees cannot select which herbivores will feed upon them. Thus, as long-lived stationary organisms, conifers must resist the onslaught of varying and multiple attackers over their lifetime. Arguably, the greatest threats to conifers are herbivorous insects and their associated pathogens. Insects such as bark beetles, stem- and wood-boring insects, shoot-feeding weevils, and foliage-feeding budworms and sawflies are among the most devastating pests of conifer forests. Conifer trees produce a great diversity of compounds, such as an enormous array of terpenoids and phenolics, that may impart resistance to a variety of herbivores and microorganisms. Insects have evolved to specialize in resistance to these chemicals -- choosing, feeding upon, and colonizing hosts they perceive to be best suited to reproduction. This review focuses on the plant-insect interactions mediated by conifer-produced terpenoids. To understand the role of terpenoids in conifer-insect interactions, we must understand how conifers produce the wide diversity of terpenoids, as well as understand how these specific compounds affect insect behaviour and physiology. This review examines what chemicals are produced, the genes and proteins involved in their biosynthesis, how they work, and how they are regulated. It also examines how insects and their associated pathogens interact with, elicit, and are affected by conifer-produced terpenoids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".